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Masters Theses, 2020-current The Graduate School

5-7-2020

Lipoprotein associated phospholipase A2 in individuals with Lipoprotein associated phospholipase A2 in individuals with

obstructive sleep apnea obstructive sleep apnea

Kendall G. Clark James Madison University

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Lipoprotein Associated Phospholipase A2 (Lp-PLA2) in Individuals with Obstructive

Sleep Apnea (OSA)

Kendall Clark

A thesis submitted to the Graduate Faculty of

JAMES MADISON UNIVERSITY

In

Partial Fulfillment of the Requirements

for the degree of

Master of Science

Department of Kinesiology

May 2020

FACULTY COMMITTEE:

Committee Chair: Trent A. Hargens, Ph. D.

Committee Members/ Readers:

Stephanie P. Kurti, Ph. D.

Christopher J. Womack, Ph. D.

ii

Acknowledgments

I would first like to thank my committee chair, Dr. Trent Hargens. This project

would not have happened without your help and encouragement. I am grateful for the

opportunity to work closely with you throughout this process. Your feedback and

instruction have made me a better writer and researcher.

I would also like to thank my other committee members, Dr. Stephanie Kurti and

Dr. Christopher Womack. Dr. Kurti, thank you for your guidance in the lab and providing

me with the best undergraduate assistants. Dr. Womack, thank you for your time and

expertise in the blood analysis process.

Additionally, I would like to thank my undergraduate assistants, Amanda Placide

and Sydney Sharp, for dedicating their time to countless hours in the lab helping me

calibrate equipment and run subjects through the protocol. These two were essential in

the data collection process.

I would not have made it through this process without my fellow classmates and

colleagues. Thank you to everyone who gave their assistance in the lab on a whim and

provided encouragement along the way. I am thankful to have gotten to spend my

graduate time at JMU with each of you and you all will always be a part of why JMU is

so special to me.

Lastly, I would like to thank all of the subjects that participated in this study. I

appreciate you dedicating your time to the lab and am very grateful to have had the

opportunity to work with each of you.

iii

Table of Contents

Acknowledgments .............................................................................................................. ii

Table of Contents…………………………………………………………………………iii

List of Tables …………………………………………………………………………….iv

List of Figures ......................................................................................................................v

Abstract .............................................................................................................................. vi

I. Introduction ......................................................................................................................1

II. Methodology .................................................................................................................13

III. Manuscript ...................................................................................................................17

IV. Appendices ..................................................................................................................39

V. References .....................................................................................................................55

iv

List of Tables

Table 1. Subject Characteristics Between OSA & Non-OSA………………………….. 36

Table 2. Physical Activity Between OSA & Non-OSA ……………………………….. 36

Table 3. Subject Characteristics Between High & Low Lp-PLA2………….………….. 37

Table 4. Physical Activity Between High & Low Lp-PLA2………………..………….. 37

v

List of Figures

Figure 1. Lp-PLA2 Between OSA & Non-OSA ……………………….……………… 38

Figure 2. Lp-PLA2 & Sedentary Minutes……………………….…………………...….38

vi

Abstract

Lipoprotein-associated Phospholipase A2 (Lp-PLA2) is a protein produced by

inflammatory cells in circulation and is associated with cardiovascular disease (CVD)

risk. Prior research demonstrates that obstructive sleep apnea (OSA) leads to increased

inflammation and is also related to CVD. Physical activity is known to reduce

inflammation and risk for both CVD and OSA. However, Lp-PLA2 has yet to be

examined in individuals with OSA who do not have any other pre-existing conditions nor

has it been associated with chronic physical activity. The purpose of this study is to

examine if there is a relationship between Lp-PLA2 mass and OSA. A secondary purpose

of this study is to determine if physical activity levels have an impact on Lp-PLA2 mass.

A total of 39 subjects with an average BMI of 29.7 (±5.3) were screened for risk of OSA

with an at home assessment device and placed into OSA and non-OSA groups. Data

collected included anthropometric data, Lp-PLA2 mass, maximal oxygen uptake

(VO2max), resting heart rate and blood pressure, heart rate variability, and an assessment

of physical activity using an accelerometer. There was no significant difference in Lp-

PLA2 mass between OSA and non-OSA groups (mean ± SD: 160.5 ±121.3 vs 124.7 ±

134.4 ng/mL). However, after taking the mean value for Lp-PLA2 mass and dividing

subjects up into two groups, one above and one below the mean, the group with the

higher Lp-PLA2 had greater waist circumference (87.8 ± 12.2 vs 100.1 ± 11.9 cm; P <

0.05), sedentary minutes (645.4 ± 161.3 vs 937.3 ± 219.1; P < 0.001), and light intensity

physical activity minutes (187.9 ± 84.5 vs 94.6 ± 27.0; P = 0.002). There appears to be no

relationship between OSA and Lp-PLA2 mass aside from a positive correlation to

sedentary minutes. However, when separated by mean Lp-PLA2 mass, it does appear that

vii

Lp-PLA2 is associated with waist circumference, sedentary time, and time in light

activity. This suggests that there could be a relationship between physical activity

behavior and Lp-PLA2, as a result of differing adiposity profile.

Chapter 1

Introduction

Lipoprotein-associated Phospholipase A2

Lipoprotein-associated Phospholipase A2 (Lp-PLA2) is a protein produced by

inflammatory cells in circulation and is associated with cardiovascular disease (CVD)

risk in individuals with metabolic disorders (Lavi, 2007). After being produced by

macrophages in atherosclerotic plaque, Lp-PLA2 is then secreted into the circulatory

system with about 80% of it bound to low-density lipoproteins (LDL) and the other 20%

bound to high-density lipoproteins (HDL) (Stafforini, 2015). Within the endothelium,

LDL becomes oxidized and yields products that are hydrolysed by Lp-PLA2, generating

oxidized phospholipids, such as lysophosphatidylcholine (lysoPC) and non-esterified

fatty acids (NEFAs) (Benitez, 2004). These products are important in mediating the

inflammatory process by upregulating expression of adhesion molecules (Shi, 2007),

activating leukocytes (Shi, 2007), and recruiting macrophages and monocytes to the

atherosclerotic plaque (Quinn, 1988). This cycle accelerates plaque formation because the

increase in inflammation produces even more Lp-PLA2, essentially upregulating itself

(Shi, 2007). One study suggests that Lp-PLA2 may be made locally by the macrophages

as Lp-PLA2 mRNA transcripts have been found in macrophages (Hakkinen, 1999).

Lp-PLA2 in normal population

Lp-PLA2 measurements can be separated into enzyme mass and activity. Both

mass and activity are significantly correlated with each other as well as with very low

density lipoprotein (VLDL), LDL, and HDL (Caslake, 2000). Both Lp-PLA2 mass and

activity stay relatively consistent in an individual, not being affected by acute

2

inflammation or infection compared to other markers of inflammation, such as high

sensitivity C-reactive protein (hsCRP) (Corson, 2008; Brilakis, 2008; Persson, 2007-epi).

This enables better clinical decisions from a single measurement and provides confidence

in trends in this inflammatory marker over a period of time (Corson, 2008). One review

found a strong positive correlation (r=0.87) between Lp-PLA2 mass and activity in

plasma samples taken from 22 subjects (Dada, 2002). In a large epidemiologic study,

there was a strong correlation between Lp-PLA2 mass and activity, with more variance

occurring between the two at higher levels (Persson, 2007-epi). The highest correlations

were seen in Lp-PLA2 activity and cholesterol, LDL, and LDL/HDL ratio, with an

inverse relationship to HDL. A weaker correlation was seen between these variables and

Lp-PLA2 mass (Persson, 2007-epi). In this same study, higher Lp-PLA2 levels were

found in smokers compared to non-smokers, individuals with a history of CVD compared

to those without, obese individuals compared to non-obese, and diabetics comparend to

non-diabetics (Persson, 2007-epi); although it should be noted that these differences were

not statistically significant. In addition, men tend to have higher levels of Lp-PLA2 mass

and activity than women (Brilakis, 2008; Persson, 2007-epi). Lp-PLA2 activity was also

lower in African Americans and Hispanics compared to Caucasians with the lowest levels

found in African American women and the highest in Caucasian males (Brilakis, 2008).

Lp-PLA2 & CVD risk

Many of the common risk factors for atherosclerosis and CVD, such as

hypertension, high LDL, smoking, and obesity, are not exhibited in up to 50% of cardiac

patients, indicating that there are other potential risk factors that need to be studied

further (Sytkowski, 1990; Dada, 2002). Compared to healthy individuals, activity and

3

mass of Lp-PLA2 is significantly increased in people with CVD (Cai, 2013). Evidence

shows that Lp-PLA2 plays a crucial role in the pathophysiology of atherosclerosis and is

indicative of future cardiovascular disease (Acevedo, 2015). Measuring Lp-PLA2 levels

is useful to evaluate the presence of atherosclerosis, especially in high risk individuals

that may have metabolic syndrome (Acevedo, 2015). Originally, >235 ng/mL of Lp-

PLA2 mass was defined as the cutoff for increased risk based off of the 50th percentile of

a healthy population (Lanman, 2006). After reviewing many Lp-PLA2 studies, one

consensus panel determined that a clinical cut point of Lp-PLA2 mass >200 ng/mL would

indicate a patient being at higher risk for cardiovascular disease (Davidson, 2008).

Vascular events alter both Lp-PLA2 mass and activity, which may be due to the

alterations in HDL/LDL levels (Delgado, 2012). While Lp-PLA2 mass and activity are

both linked to lipid levels, Lp-PLA2 mass also has a strong link with cholesterol and

triglyceride levels (Delgado, 2012). One study found that Lp-PLA2 mass was higher in

individuals with coronary artery disease (CAD) and subjects post-myocardial infarction

compared to a control group (Caslake, 2000). Interestingly, the Lp-PLA2 mass levels

were higher in individuals with CAD even though LDL was not significantly different

from the control group. This indicates that plasma Lp-PLA2 mass was a strong predictor

of risk, independent of common risk factors (LDL, HDL, smoking, and BP) in the CAD

group (Caslake, 2000). It was speculated that as LDL is cleared from plasma, Lp-PLA2

would be cleared at the same rate. However, Lp-PLA2 has also been found bound to a

small dense LDL subtype that has a prolonged half-life, which could explain the elevated

Lp-PLA2 mass in these subjects regardless of LDL (Guerra, 1997).

4

Lp-PLA2 activity and mass has been associated as an independent and significant

indicator of metabolic syndrome and inflammation, possibly increasing the risk of CVD

(Persson, 2007; Acevedo, 2015). Regardless of metabolic syndrome, higher Lp-PLA2

levels have been found to increase risk of CVD (Persson, 2007). However, high Lp-PLA2

levels in combination with metabolic syndrome has the highest risk for CVD (Persson,

2007). In addition, Lp-PLA2 appears to be influenced by weight, metabolic state and

unfavorable circulating lipid profiles (increased oxidized LDL and triglycerides)

(Jackisch, 2018). These responses are exacerbated in individuals with type 2 diabetes,

which also increases risk for CVD (Jackisch, 2018).

The expression of Lp-PLA2 was observed in coronary arteries from 25 subjects

who died from sudden cardiac death. Plaque samples with increased Lp-PLA2 were

associated with thin, fibrous caps or ruptured plaques compared to more stable lesions

that had less Lp-PLA2 (Kolodgie, 2006). An increased Lp-PLA2 mass and activity and

lysoPC levels in carotid artery plaques of patients with symptomatic cerebrovascular

disease has also been associated with markers of tissue oxidative stress, inflammation,

and instability. (Mannheim, 2008) This suggests that there may be a relationship between

Lp-PLA2 and plaque instability (Kolodgie, 2006; Mannheim, 2008).

A large portion of patients who suddenly die from CVD present no symptoms

prior to their event (Go, 2014). The Framingham Risk Score (FRS) has been used to help

detect CVD risk but still many patients are misclassified (NCEP, 2002). In a previous

study, many of those who were classified as low risk by the FRS were still classified as

high risk by Lp-PLA2 mass (>200 ng/mL) (Hargens, 2014). This suggests that Lp-PLA2

mass may be indicative of CVD independently of other risk factors.

5

A meta-analysis of 25 clinical trials found elevated Lp-PLA2 caused an almost

two-fold increase in risk for future and recurring CVD events (Corson, 2008). Thus, it

was determined that Lp-PLA2 is a relevant risk factor to identify individuals at a high risk

for CVD and those who could benefit from intensive lipid-lowering interventions

(Corson, 2008). Another meta-analysis of 32 clinical studies found increased relative

risks in individuals with elevated Lp-PLA2 levels for CHD, ischemic stroke, vascular

mortality, and non-vascular mortality (Thompson, 2010). There have also been observed

elevations in Lp-PLA2 in individuals with proven coronary artery disease, independently

of LDL, HDL, smoking, and systolic blood pressure (Caslake, 2000). This adds to the

evidence that Lp-PLA2 levels may be a valuable addition to traditional risk factors in

assessing CVD risk as been suggested by a consensus panel (Davidson, 2008).

Obstructive Sleep Apnea (OSA)

Obstructive Sleep Apnea (OSA) can be described as recurrent episodes of full or

partial collapse of the airways during sleep, leading to decreased ventilation, frequent

arousals, sleep fragmentation, and oxyhemoglobin desaturation (Somers, 2008). An

apnea event can be described as a complete restriction of airflow for greater than 10

seconds while a hypopnea event is defined as a reduction in airflow to less than 50% of

normal airflow (Somers, 2008). Diagnosis and determination of severity of sleep apnea is

defined by the apnea-hypopnea index (AHI), which is the number of apnea or hypopnea

events per hour (mild OSA: ≥ 5 AHI; moderate OSA: ≥ 15 AHI; severe OSA ≥ 30 AHI)

(Young, 2002). Recent prevalence estimates of moderate to severe sleep apnea are 10%

among 30–49-year-old men; 17% among 50–70-year-old men; 3% among 30–49-year-

old women; and 9% among 50–70 year-old women (Peppard, 2013). These estimates

6

represent a significant increase of 14% to 55% over the last two decades depending on

the subgroup (Peppard, 2013). The Wisconsin Sleep Cohort measured AHI over a period

of eight years and found the greatest increase in AHI across individuals who were

habitual snorers, had a body mass index (BMI) ≥ 30, and those who were 45-60 years of

age (Young, 2002). In addition, it is predicted that about 80% of individuals with

moderate to severe OSA are undiagnosed (Lee, 2008) and even those who are diagnosed

often choose not to accept treatment (Weaver, 2008). When left untreated, OSA can lead

to daytime sleepiness, cognitive dysfunction, and decrease in quality of life (Punjabi,

2008).

Sleep Apnea and CVD

Interrupted sleep, hypoxemia, and daytime sleepiness due to OSA induces an

increase in oxidative stress, inflammation, and endothelial apoptosis, which contributes to

endothelial dysfunction, eventually leading to atherosclerosis or CVD if left untreated

(Somers, 2008; Atkeson, 2009; Savransky, 2007). Individuals with OSA have been

shown to have an increased sympathetic activation, leading to an increased resting heart

rate (Narkiewicz, 1998). These individuals have also been seen to have decreased heart

rate variability and increased blood pressure variability (Narkiewicz, 1998). In addition,

OSA has been associated with insulin resistance, independent of BMI (Punjabi, 2004).

Lastly, the forced inspiration during sudden arousals at night creates dramatic pressure

change, causing a negative intrathoracic pressure environment and increased stress on the

heart (Somers, 2008). About 50% of patients who have OSA also have hypertension

(Silverberg, 1998). Even after controlling for age, sex, BMI, and hypertension

7

medications, the Wisconsin Sleep Cohort study found a dose response relationship

between blood pressure and OSA (Peppard, 2000).

One study found that, in middle aged males with OSA, those who were not treated

for their condition had a significantly higher CVD incidence (56.8%) compared to those

who were treated for their OSA (6.7%) (Peker, 2002). They concluded that individuals

with OSA have an increased risk for CVD, independent of age, BMI, blood pressure, and

smoking habits. However, those who are treated for their OSA greatly reduced their risk

of developing CVD (Peker, 2002).

Due to the metabolic damage caused by apnea events, OSA has also been linked

to type 2 diabetes. One study found that sleep disordered breathing was independently

related to glucose intolerance and insulin resistance and that the severity of the sleep

disordered breathing was also associated with the degree of insulin resistance (Punjabi,

2004). These hypoxic events have been linked to an increase in proinflammatory

cytokines, specifically interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-ɑ),

which has been linked to insulin resistance and increased risk for type 2 diabetes

(Huiguo, 2000; Punjabi, 2004). Individuals with sleep disordered breathing have also

shown to have increased sympathetic neural activity (Peled, 1998), which can increase

glycogen breakdown and gluconeogenesis and disrupt glucose homeostasis (Punjabi,

2004). In addition, sleep-disordered patients have increased levels of cortisol (Bratel,

1999), which has been shown to increase glucose levels and insulin concentration (Plat,

1999).

Weight and Sleep Apnea

8

Obesity has consistently been associated with OSA and has even been said to be

one of the most important risk factors for sleep disordered breathing (Young, 2002,

Wolk, 2003). About 40% of obese indivuals have significant sleep apnea and about 70%

of indiviuals with OSA are obese (Vgontzas, 1994). One study found that a 10% increase

in weight increased the odds of developing sleep apnea 6-fold (Peppard, 2000). In

addition, a 10% decrease in weight was associated with a 26% decrease in AHI (Peppard,

2000). Research suggests that obesity leads to the narrowing and altering of function of

the airways (Horner, 1989; Schwartz, 1991). Obese individuals have large fat deposits

surrounding the collapsible part of the pharynx, and this is exacerbated in individuals

with OSA compared to weight-matched controls without OSA (Horner, 1989). Weight

loss has been associated with a decrease in airway collapsibility in individuals who have

sleep apnea (Schwartz, 1991). Male patients who have OSA have about 50% higher

leptin levels than weight-matched individuals without OSA (Phillips, 2000). Thus, it is

likely that leptin resistance is especially increased in individuals with OSA, potentially

leading to even greater weight gain and progression of OSA (Wolk, 2003). In healthy

individuals who experience weight gain, the possibility of developing OSA is increased.

In overweight individuals with OSA, further weight gains accelerate the progression of

OSA (Young, 2002; Peppard, 2000). The greater the increase in body weight or waist

circumference, the greater the progression of OSA and vice versa (Young, 2002;

Peppard, 2000). In addition, individuals who currently have OSA and gain weight

experience an increase in OSA severity independent of other factors such as age, body

composition, and smoking habits (Peppard, 2000).

Exercise & Sleep Apnea

9

Similar to baseline weight, habitual physical activity levels predict development

of OSA. Awad et al. observed that active individuals exhibited a decreased incidence of

OSA in an 8-year follow up compared to sedentary individuals. Furthermore, decreasing

exercise over time was associated with an increase in AHI (Awad, 2012). Individuals

with OSA tend to be more sedentary regardless of levels of obesity or daytime sleepiness

(Hargens, 2019). In addition to just being active, exercise training volume exhibits a

dose-response relationship for likelihood of OSA (Peppard, 2004).

Exercise is also beneficial in the reduction of obesity, blood pressure, and CVD,

which are all associated with OSA (Young, 2002). In addition to these benefits, AHI

levels may be reduced by up to 50% following chronic exercise training in those who

have sleep apnea (Norman, 2000; Sengul, 2011). This may be due to general

improvements in strength and fatigue resistance of the airways (Vincent, 2002). In

sedentary, obese individuals with untreated moderate to severe sleep apnea, significant

improvements in AHI were observed following an exercise training program, even

without a significant reduction in body weight (Kline, 2011). There were also

improvements in both objective and subjective sleep quality, suggesting that exercise

training may be beneficial (Kline, 2011). Similarly, another study found that exercise

training led to improvements in AHI, sleep efficiency, and daytime sleepiness,

independent of changes in BMI (Iftikhar, 2014). A similar study in OSA patients found

that regular exercise training improved BMI, along with aerobic capacity and quality of

life (Norman, 2000). A meta-analysis of exercise intervention studies also observed a

reduction in AHI regardless of types, durations, or frequencies of exercise or continuous

positive airway pressure (CPAP) use (Aiello, 2016).

10

Chronic exercise is associated with an increase in slow wave sleep (SWS), total

sleep time; and decreases in rapid eye movement (REM) sleep, sleep onset latency

(SOL), and wake after sleep onset (WASO) (Kubitz, 1996). In previously sedentary

individuals, a two month exercise intervention increased vagal activity and decreased

sympathetic activity during sleep (Pichot, 2002). The exact physiological mechanisms of

how exercise improves OSA are unknown and more research is needed to determine how

exercise improves OSA independent of weight loss.

Exercise intensity is also associated with prevalence and severity of OSA.

Vigorous physical activity for >3 hours has been associated with a larger decrease in the

prevalence of OSA than the same duration of exercise performed at a moderate intensity

(Quan, 2007). These outcomes were more pronounced in males and obese individuals

(Quan, 2007). These findings were similar to another study who also observed increased

planned exercise associated with less severe OSA (Peppard, 2004). Both studies

determined that benefits were seen with about 3-6 hours of exercise per week or at least 3

hours of vigorous intensity, independent of weight loss and daytime sleepiness (Quan,

2007; Peppard, 2004).

OSA & Lp-PLA2

In recent years research has evaluated the relationship between OSA and Lp-

PLA2 concentration. In one study looking at CVD risk among individuals with OSA,

COPD, or overlap syndrome (having both OSA and COPD), they found that Lp-PLA2

mass was elevated in all 3 groups, with the highest concentration in the overlap syndrome

group, followed by the OSA group (Badr, 2014). In a similar study, Lp-PLA2 mass was

elevated in individuals with OSA and in individuals with metabolic syndrome, but those

11

who had OSA and metabolic syndrome had the highest concentration of Lp-PLA2

(Moise, 2018). Another study separated the OSA subjects into mild, moderate, and severe

categories and found that Lp-PLA2 mass increased with OSA severity and also increased

with the presence of CVD in addition to OSA (Xu, 2020). Lastly, a study that solely

studied OSA and its correlation to Lp-PLA2 mass, separated 50 male patients diagnosed

with OSA into quartiles based on their number of arousals. They found that those in the

highest quartile had the highest Lp-PLA2 (Bekci, 2011).

Thus, it is apparent that there is a relationship between Lp-PLA2 and OSA. It is

also known that Lp-PLA2 concentration and presence of OSA are typically higher in

individuals who are at risk for CVD and in individuals who are overweight. In addition to

these risk factors, OSA has been shown to be both more prevalent and more severe in

those who lead a sedentary lifestyle.

Purpose

It has not been examined if chronic physical activity influences Lp-PLA2

concentration. Additionally, there needs to be more research in the relationship between

Lp-PLA2 and individuals with OSA who have no other pre-existing conditions.

Therefore, the primary purpose of this study is to determine whether there is an increase

in Lp-PLA2 concentration in individuals with OSA who have no other chronic conditions.

In addition, we will determine if there is a relationship between Lp-PLA2 concentration

and physical activity. We hypothesize that individuals with OSA will have higher Lp-

PLA2 concentrations. In addition, individuals Lp-PLA2 concentration will be associated

with chronic physical activity, with more active individuals exhibiting a lower

concentration of Lp-PLA2.

12

Limitations

One limitation in this study includes using an at home screening device to

diagnose OSA. However, despite this being an at-home screening tool, it has been

validated against hospital based polysomnography (Ng, 2009). We are assuming that the

equipment used in this study provides valid assessments of the variables we are observing

and that the participants understand our instructions and are knowledgeable in how to

properly assemble the at home screening device. The questionnaires utilized for this

study are also assuming that participants are disclosing accurate information about their

health history and physical activity. Additionally, we are limiting our subjects to

individuals who do not have other pre-existing chronic diseases. Lastly, placing an age

range on our subjects means that we will not be able to generalize our results to

individuals who are outside that age range.

13

Chapter 2

Methodology

Subjects

Participants were recruited through bulk email requests to all JMU faculty and

students. Thirty-nine subjects were recruited for the study (11 individuals with OSA and

28 control subjects). Inclusion criteria for both the experimental and control groups

included subjects that have been cleared to exercise by the Physical Activity

Questionnaire-Plus (PAR-Q+) and are between the ages of 18 and 57 years old.

Individuals in the experimental group had an AHI of at least 5. Individuals in the control

group had an AHI of <5. Exclusion criteria included participants who had a current

diagnosis of any cardiovascular, metabolic, or pulmonary disease as well as participants

who were pregnant (due to the low dose of radiation from DEXA).

Experimental methods

This study was part of a larger study that looked at airway responsiveness and

nitric oxide (NO) exhalation in individuals with OSA following a maximal exercise bout.

Subjects visited the laboratory a total of 2 times. During the first visit, after explaining

and signing a subject consent form, subjects completed a series of questionnaires,

including a PAR-Q+, International Physical Activity Questionnaire (IPAQ), Epworth

Sleepiness Scale (ESS), and Berlin Questionnaire. The IPAQ is validated in adults to

assess moderate to vigorous physical activity (MVPA) per week both in leisure time and

work related physical activity (Craig, 2003). The PAR-Q+ is a validated, self-guided

physical activity readiness questionnaire (Riebe, 2018). If the participant reported that

they do not regularly participate in planned exercise, they must also have no signs or

14

symptoms of cardiovascular disease, metabolic or renal disease. If they did have signs

and symptoms or were asymptomatic but have previously been diagnosed with the

aforementioned diseases, they were excluded from the study. Participants that engaged in

regular physical activity, were asymptomatic and had never been diagnosed with renal,

metabolic or cardiovascular diseases were cleared by the American College of Sports

Medicine (ACSM) guidelines to undergo the incremental exercise test to exhaustion to

determine peak oxygen uptake (VO2peak), even if they have sleep apnea. The Berlin

Questionnaire and ESS assessed the subjects snoring habits and daytime sleepiness

(Kang, 2013; Johns, 1992). Anthropometric variables were then obtained including,

height, weight, and waist/neck circumferences. Cardiorespiratory fitness was determined

using a graded cycle ergometer VO2max test. Subjects were then sent home with an

unattended, home sleep evaluation using a type III validated device (ApneaLink™ Plus,

RedMed Corp., San Diego, CA) to assess for the likely presence of OSA (Ng, 2009).

Research staff instructed the patient on the proper setup and use of the at-home screening

device. The device is composed of a pulse oximeter, which was worn on the end of an

index finger, and a nasal cannula, which was worn over the face, and into the nose to

measure airflow. This device is harmless and painless to wear. The results of this test will

objectively divide the subjects into OSA and non-OSA control groups. Subjects were also

sent home with an accelerometer (Actigraph GT3X+, Actigraph Corp., Pensacola, FL) to

assess their 7-day physical activity. Subjects were asked to wear the device on their waist

at all times, except while sleeping and showering. Accelerometers have been validated to

assess MVPA per week (Kelly, 2013). On their second visit, a fasted, resting venous

blood draw was taken. This was followed by a heart rate variability assessment that also

15

included a resting blood pressure measurement in the supine position. Lastly, a Dual-

energy X-ray absorptiometry (DEXA) analysis using the General Electrics (GE) Lunar

iDEXA was performed to assess body composition (body fat percentage and lean mass).

Fasting blood collection

10 ml of blood was drawn from an antecubital vein using clean venipuncture.

Blood samples were immediately centrifuged for 20 min at 1,500xg and 4°C to obtain

platelet-poor plasma. Plasma aliquots were frozen and stored at - 20°C until assayed.

These samples were used to assess Lp-PLA2 mass.

Blood Analysis

An Enzyme-Linked Immunosorbent Assay (ELISA) kit was used to determine

Lp-PLA2 mass. Plasma samples were pipetted into the wells and the target protein

becomes bound to the wells by an immobilized antibody after sitting for 2.5 hours. Cells

are then washed four times to remove any unbound antibodies. The wells are then washed

with another antibody, sandwiching the Lp-PLA2 molecules between the two antibodies

after sitting for 1 hour. Cells are then washed four times again to remove any unbound

antibodies. A HRP-streptavidin solution was then pipetted into the wells with the

absorbance of this enzyme being directly proportional to the Lp-PLA2 concentration in

the sample. After 45 minutes, the wells were washed for a third time. A TMB substrate is

then added to the wells and a color develops, proportional to the concentration of Lp-

PLA2. A Stop solution is then added and the color turns from blue to yellow with the

intensity of the color being measured at 450 nm. (Sigma-Aldrich ELISA Kit Information;

Dada, 2002)

Graded Exercise Test

16

A maximal ramped (15 Watts per minute ramp rate) exercise test was completed

on an electronically braked, cycle ergometer. Metabolic responses were measured

continuously using a metabolic cart (Parvo Medics TrueOne 2400, Parvo Medics, Salt

Lake City, UT). Heart rate was measured continuously using a Polar V800 watch and

Polar H10 heart rate chest strap (Polar Electro). Rating of perceived exertion was

measured every minute using the Borg 6-20. Dyspnea ratings were also recorded every

minute using a dyspnea scale from 1-10. Blood pressure was taken manually every 3

minutes during the test. Subjects were instructed to keep their revolutions per minute

(RPM) above 50 and the test was terminated either by the subject voluntarily or if 50

RPMs could not be maintained.

Statistical Analysis

All statistical analyses were performed using IBM SPSS Statistics (version 26.0).

Independent sample t tests were used to assess group differences in Lp-PLA2 mass.

Pearson correlations were calculated to determine relationships between Lp-PLA2, OSA,

physical activity and sedentary behavior. A value of P < 0.05 was considered statistically

significant a priori.

17

Chapter 3

Manuscript

Lipoprotein Associated Phospholipase A2 (Lp-PLA2) in Individuals with

Obstructive Sleep Apnea (OSA)

Authors: Kendall G. Clark, Stephanie P. Kurti, Christopher J. Womack, Trent A.

Hargens

Institution: James Madison University, Harrisonburg, Virginia, 22807

Contacts: Kendall G. Clark, clarkkg@dukes.jmu.edu

Trent A. Hargens, hargenta@jmu.edu

Stephanie P. Kurti, kurtisp@jmu.edu

Christopher J. Womack, womackcx@jmu.edu

Address of Correspondence

Trent A. Hargens, Ph.D.

Department of Kinesiology

James Madison University

Harrisonburg VA, 22807

Phone: (540) 568-6145

Email: hargenta@jmu.edu

18

Abstract

Introduction: Lipoprotein-associated Phospholipase A2 (Lp-PLA2) is a protein produced

by inflammatory cells in circulation and is associated with cardiovascular disease (CVD)

risk. Prior research demonstrates that obstructive sleep apnea (OSA) leads to increased

inflammation and is also related to CVD. Physical activity is known to reduce

inflammation and risk for both CVD and OSA. However, Lp-PLA2 has yet to be

examined in individuals with OSA who do not have any other pre-existing conditions nor

has it been associated with chronic physical activity. The purpose of this study was to

examine if there is a relationship between Lp-PLA2 mass and OSA. A secondary purpose

of this study was to determine if physical activity levels have an impact on Lp-PLA2

mass.

Methods: A total of 39 subjects with an average BMI of 29.7 ±5.3 were screened for risk

of OSA with an at home assessment device and placed into OSA and non-OSA groups.

Data collected included anthropometric data, Lp-PLA2 mass, maximal oxygen uptake

(VO2max), resting heart rate and blood pressure, heart rate variability, and an assessment

of physical activity using an accelerometer.

Results: There was no significant difference in Lp-PLA2 mass between OSA and non-

OSA groups (160.5 ±121.3 vs 124.7 ± 134.4 ng/mL). However, after taking the mean

value for Lp-PLA2 mass and dividing subjects up into two groups, one above and one

below the mean, the group with the higher Lp-PLA2 had greater waist circumference

(87.8 ± 12.2 vs 100.1 ± 11.9 cm; P < 0.05), sedentary minutes (645.4 ± 161.3 vs 937.3 ±

219.1; P < 0.001), and light intensity physical activity minutes (187.9 ± 84.5 vs 94.6 ±

27.0; P = 0.002).

19

Conclusions: There appears to be no relationship between OSA and Lp-PLA2 mass aside

from a positive correlation to sedentary minutes. However, when separated by mean Lp-

PLA2 mass, it does appear that higher Lp-PLA2 is associated with waist circumference,

sedentary time, and time in light activity. This indicates that there could be a relationship

between physical activity behavior and Lp-PLA2, as a result of differing adiposity profile.

20

Introduction

Lipoprotein-associated Phospholipase A2 (Lp-PLA2) is a protein produced by

inflammatory cells in circulation and is associated with increased cardiovascular disease

(CVD) risk in individuals with metabolic disorders (Lavi, 2007). This biomarker is bound

primarily to low density lipoprotein (LDL) and causes an acceleration in plaque

formation, increasing inflammation and essentially upregulating itself (Stafforini, 2015;

Shi, 2007). Lp-PLA2 concentration can be separated into enzyme mass and activity,

which are both associated with very low density lipoprotein (VLDL), LDL, and high

density lipoprotein (HDL), with Lp-PLA2 mass also being correlated with triglyceride

and cholesterol levels (Caslake, 2000; Delgado, 2012). Lp-PLA2 concentration stays

relatively consistent, as it is not affected by acute inflammation compared to other

markers of inflammation, such as high sensitivity C-reactive protein (hsCRP) (Corson,

2008; Brilakis, 2008; Persson, 2007-epi). However, Lp-PLA2 concentration can be

influenced by chronic inflammation. Higher levels of the biomarker are found in men,

smokers and individuals with a history of CVD, obesity, diabetes, or metabolic syndrome

(Persson, 2007-epi; Persson, 2007; Brilakis, 2008; Jackisch, 2018) and has also been

associated with plaque instability (Kolodgie, 2006; Mannheim, 2008). Elevated Lp-PLA2

increases risk for developing CVD or experiencing recurring CVD events, even in those

determined to be low risk (Thompson, 2010, Corson, 2008, Hargens, 2014). This adds to

the evidence that Lp-PLA2 levels may be a valuable prognostic tool for CVD events in

addition to traditional risk factors.

With this research, it seems that Lp-PLA2 is associated with many risk factors and

conditions that often lead to or are caused by chronic inflammation. Obstructive Sleep

21

Apnea (OSA), which can be described as recurrent episodes of full (apnea) or partial

(hypopnea) collapse of the airways during sleep, results in systemic inflammation

(Somers, 2008; Atkeson, 2009; Savransky, 2007). Apneas and hypopneas leads to

decreased ventilation, frequent arousals, sleep fragmentation, and oxyhemoglobin

desaturation (Somers, 2008). Diagnosis and severity of sleep apnea is determined by the

apnea-hypopnea index (AHI), which is the number of apneas and hypopneas per hour of

sleep. Interrupted sleep due to OSA induces an increase in oxidative stress, inflammation,

and endothelial apoptosis, which contributes to endothelial dysfunction, eventually

leading to atherosclerosis or CVD if left untreated (Atkeson, 2009; Savransky, 2007).

The link between OSA, inflammation, and CVD suggests a possible role of Lp-PLA2.

This has been demonstrated in recent studies finding that Lp-PLA2 mass is higher in

individuals with OSA, and increased with OSA severity (Badr, 2014; Moise 2018; Xu,

2020, Bekci, 2011). However, many of these studies examined an older population with

OSA and other co-morbid conditions.

While OSA may increase inflammatory markers, including Lp-PLA2, habitual

physical activity is anti-inflammatory and has been associated with a decrease in

traditional risk factors (Kokkinos, 2012). In regard to OSA, individuals with the

condition tend to be more sedentary, regardless of BMI or daytime sleepiness (Hargens,

2019). However, active individuals exhibited a decreased incidence of OSA in an 8-year

follow up compared to sedentary individuals, while individuals who decreased exercise

over time exhibited a significant increase in AHI (Awad, 2012). Since physical activity

reduces indicators of inflammation, the impact that physical activity may have on Lp-

PLA2 has not been explored.

22

Therefore, the primary purpose of this study is to determine whether there is an

increase in Lp-PLA2 concentration in individuals with OSA who have no other chronic

conditions. In addition, we will determine if there is a relationship between Lp-PLA2

concentration and physical activity. It is hypothesized that individuals with OSA will

have higher Lp-PLA2 concentration. In addition, more active individuals will exhibit a

lower concentration of Lp-PLA2.

Methodology

Subjects

Participants were recruited through bulk email requests to all JMU faculty and

students. In addition to subjects recruited through these methods, previous data was

added to the sample pool (6 individuals with OSA and 10 control subjects) from an

unpublished study using identical methods. Thirty-nine subjects (18-57 years of age)

were used in the analysis for this study (11 individuals with OSA and 28 control

subjects). Inclusion criteria for both the experimental and control groups included

subjects that have been cleared to exercise by the Physical Activity Questionnaire-Plus

(PAR-Q+). Individuals in the experimental group had an AHI of at least 5. Individuals in

the control group had an AHI of <5. Exclusion criteria included participants with known

cardiovascular, metabolic, or pulmonary disease as well as participants who were

pregnant (due to the low dose of radiation from DEXA).

Experimental methods

This study was part of a larger study evaluating airway responsiveness and nitric

oxide (NO) exhalation in individuals with OSA following a maximal exercise bout.

Subjects visited the laboratory a total of 2 times. During the first visit, subjects completed

23

the informed consent and initial questionnaires, including a PAR-Q+, International

Physical Activity Questionnaire (IPAQ), Epworth Sleepiness Scale (ESS), and Berlin

Questionnaire. The IPAQ is validated in adults to assess moderate to vigorous physical

activity (MVPA) per week both in leisure time and work related physical activity (Craig,

2003). The PAR-Q+ is a validated, self-guided physical activity readiness questionnaire

(Riebe, 2018). The Berlin Questionnaire and ESS assessed the subjects snoring habits and

daytime sleepiness (Kang, 2013; Johns, 1992). Anthropometric variables were then

obtained including, height, weight, and waist/neck circumferences. Cardiorespiratory

fitness was determined using a graded cycle ergometer maximal oxygen uptake (VO2

max) test. Subjects were then sent home with an unattended, home sleep evaluation using

a type III validated device (ApneaLink™ Plus, RedMed Corp., San Diego, CA) to assess

for the likely presence of OSA (Ng, 2009). Research staff instructed the patient on the

proper setup and use of the at-home screening device. The device is composed of a pulse

oximeter, which was worn on the end of an index finger, and a nasal cannula, which was

worn over the face, and into the nose to measure airflow. The results of this test were

used to objectively divide the subjects into OSA and non-OSA control groups. Subjects

were also sent home with an accelerometer (Actigraph GT3X+, Actigraph Corp.,

Pensacola, FL) to assess their 7-day physical activity. Subjects were asked to wear the

device on their waist at all times, except while sleeping and showering. Accelerometers

have been validated to assess MVPA per week (Kelly, 2013). On their second visit, a

fasted, resting venous blood draw was taken. This was followed by a Dual-energy X-ray

absorptiometry (DEXA) analysis using the General Electrics (GE) Lunar iDEXA to

assess body composition (body fat percentage and lean mass).

24

Fasting blood collection

10 ml of blood was drawn from an antecubital vein using clean venipuncture.

Blood samples were immediately centrifuged for 20 min at 1,500xg and 4°C to obtain

platelet-poor plasma. Plasma aliquots were frozen and stored at - 20°C until assayed.

These samples were used to assess Lp-PLA2 mass.

Blood Analysis

An Enzyme-Linked Immunosorbent Assay (ELISA) kit was used to determine

Lp-PLA2 mass (Sigma-Aldrich). All samples were measured in duplicate at minimum.

Statistical Analysis

All statistical analyses were performed using IBM SPSS Statistics (version 26.0).

Independent sample t tests were used to assess group differences in Lp-PLA2 mass.

Pearson correlations were calculated to determine relationships between Lp-PLA2, AHI,

physical activity, and sedentary behavior variables. A value of P < 0.05 was considered

statistically significant a priori.

Results

By design, the OSA group had a significantly higher AHI than the non-OSA

group. Subject characteristics for the OSA and non-OSA groups are listed in Table 1. The

OSA group was older than the non-OSA group (P = 0.001). There were no group

differences in any body composition variable, however there was a trend for a greater

neck circumference in the OSA group (P = 0.05). There was no correlation between Lp-

PLA2 mass and age (r=0.104, P=0.536) or AHI (r=0.122, P=0.458). Independent sample

t-test revealed no difference in Lp-PLA2 mass between the OSA and non-OSA groups,

25

which did not change when age was used as a covariate in a one way analysis of variance

(P=0.45). (Figure 1)

Lp-PLA2 Mass & Physical Activity

There was a positive correlation between Lp-PLA2 mass and sedentary minutes

per day (r=0.405, P<0.05), based on an analysis of 25 subjects, as those with insufficient

accelerometer data were not included in this analysis. (Figure 2) Physical activity

between groups did not differ between the OSA and non-OSA groups, with the exception

of the OSA group having fewer moderate intensity minutes per day (P = 0.039).

However, when controlled for age this difference was no longer significant. (Table 2)

Due to the positive association seen between sedentary time and Lp-PLA2 in the

entire sample, we sought to explore the relationship between sedentary behavior and Lp-

PLA2 further. The sample of 25 subjects were split into two groups based on whether they

were above or below the mean value for Lp-PLA2 mass (134.7 ng/mL). The mean was

chosen due to the fact that our subjects were healthy and relatively young, which resulted

in overall lower Lp-PLA2 compared to other studies, and only four subjects with an Lp-

PLA2 mass over 200 ng/mL. The two groups did not differ in age, AHI, BMI, or % body

fat. Waist circumference was greater in the higher Lp-PLA2 group compared to the lower

Lp-PLA2 group (P<0.05). (Table 3) Those in the higher Lp-PLA2 group had a greater

number of sedentary minutes per day (<0.001) and fewer light intensity PA minutes per

day compared to the lower Lp-PLA2 group (P=0.002). Total moderate to vigorous

intensity physical activity and average step count per day did not differ between groups.

(Table 4)

26

Discussion

Results from this study suggest that OSA may not impact Lp-PLA2 mass in a

younger, healthier cohort, as we found no difference in Lp-PLA2 in those at high

likelihood for OSA compared to those screened as negative for likely presence of OSA. It

is important to note that our OSA group had a mean OSA severity rated as “mild”, with

only four reaching a moderate severity and none reaching severe. Of these four moderate

OSA subjects, the mean Lp-PLA2 was 182 ng/mL and only three of them exceeded 200

ng/mL. This may have impacted our ability to observe a relationship between OSA

severity and Lp-PLA2. In addition, our sample was relatively young, with ages in the

OSA group ranging from 21-57. Thus, some subjects may have only been exposed to the

potential inflammatory effects of OSA for a short period of time.

In previous clinical studies, Lp-PLA2 was typically evaluated in relation to OSA

and another chronic condition, such as CVD, COPD, and metabolic syndrome (Xu, 2020;

Badr, 2014; Moise, 2018). In each of these studies, Lp-PLA2 was found in the greatest

amount in the groups diagnosed with OSA in addition to another condition. In studies

that split OSA groups into severities, the most severe group had the greatest increase in

Lp-PLA2 (Xu, 2020; Bekci, 2011). These previous studies used subjects with moderate to

severe sleep apnea, which would also lead us to expect greater Lp-PLA2 concentrations

than the present study (Moise, 2018; Badr, 2014; Bekci, 2011) as Xu et al. (2020) have

observed that Lp-PLA2 mass is only increased in individuals with moderate and severe

sleep apnea. The present study sought to evaluate the effects of OSA independent of

other chronic conditions that increase inflammation, such as CVD. Thus, prior findings

may have been influenced by comorbid conditions and OSA per se may not have a large

27

impact on Lp-PLA2. Additionally, our OSA group was younger (44.1 ± 12.9 years) than

all of the aforementioned studies with our control group being even younger (28.6 ± 10.8

years), which could have contributed to the similar Lp-PLA2 between groups.

The interesting finding of the current study was the relationship between Lp-PLA2

and sedentary behavior, independent of OSA. We observed that in those with greater

sedentary behavior, Lp-PLA2 was higher, Additionally, those with higher Lp-PLA2 had

fewer minutes of light intensity PA and greater waist circumference. While both groups

would be classified as being “low active” based on step counts (Tudor-Locke, 2013), and

are meeting current physical activity recommendations in terms of MVPA (Riebe, 2018),

the group with higher Lp-PLA2 had a lower overall physical activity profile with less

light activity minutes and greater sedentary minutes. This decrease in overall activity

profile may contribute to the greater waist circumference observed, which may correlate

to the greater Lp-PLA2.

Habitual physical activity is anti-inflammatory and has been associated with a

decrease in traditional risk factors (Kokkinos, 2012). Data from the Harvard Alumni

Health Study suggests that while light intensity activities are not associated with reduced

mortality rates, moderate intensity is somewhat beneficial, and vigorous intensity

significantly reduces mortality rates (Lee, 2000). In contrast, one systematic review found

that while moderate to vigorous intensity activities provide more benefits per unit of time,

light intensity physical activity offers some reduction of cardiovascular risk and all-cause

mortality (Chastin, 2019). Sedentary time, independent of total activity levels, is also an

important risk factor for CVD and all-cause mortality with more than 2.5 times greater

risk in those who accumulate 10 hours/day compared to 6.5 hours/day (Dohrn, 2018).

28

Even intermittent breaks in sedentary time is beneficially correlated to waist

circumference and cardiometabolic biomarkers (Healy, 2011). In the present study, both

groups exceeded 10 hours/day of sedentary time on average, regardless of if groups were

separated based on presence of OSA (13.6 hours vs 12.6 hours) or concentration of Lp-

PLA2 (10.8 hours vs 15.6 hours).

With much of the research and data published, including the national guidelines,

focusing on the importance of MVPA, this somewhat novel information on sedentary

time and light intensity PA is an important contribution to this area of literature. With

many Americans struggling to even meet the guidelines it is important to research how

our sedentary time is impacting our mortality risk and what even the smallest bit of

activity can do to help.

Physical activity has also been a predictor of waist circumference with those who

engage in higher levels of physical activity typically having lower abdominal adiposity

(Ekelund, 2011). We found that, in addition to a lack of light PA and an excess of

sedentary time, the high Lp-PLA2 group also appeared to have a larger waist

circumference, regardless of BMI or body fat percent. Although BMI is typically used to

determine health risks, waist circumference may be a better determinant of predicting

obesity-related health risks, with most individual risk factors for CVD having a higher

correlation to waist circumference than BMI (Janssen, 2004; Zhu, 2002). In addition to

obesity and visceral adiposity, inflammatory cytokines such as tumor necrosis factor

alpha (TNF-ɑ), interleukin 6 (IL-6), and C-reactive protein (CRP) have been associated

with waist circumference, indicating that an increase in waist circumference can create an

increase in inflammation (Park, 2005). When comparing normal weight women to

29

overweight/obese women, the overweight/obese group had significant increases in waist

circumference and Lp-PLA2 in addition to other indicators of oxidative stress (Paik,

2015). A separate study observed an increase in waist circumference, inflammatory

biomarkers, including Lp-PLA2, and a decrease in physical activity among men and

women who developed CVD across a mean follow-up of 10 years compared to those who

did not (Rana, 2011). One study indicates that Lp-PLA2 is actively produced in adipose

tissue and is also expressed in greater amounts specifically in abdominal subcutaneous

tissue (Jackisch, 2018). Weight loss interventions resulting in a reduction of waist

circumference have also been associated with a reduction in Lp-PLA2 (Tzotzas, 2008).

Our findings indicate similar results that individuals with greater waist circumferences

exhibited greater Lp-PLA2 concentrations. This adds to the evidence that location of

adipose tissue may contribute greater risk for obesity related conditions.

One limitation of the present study is that there was a relatively small sample size

with only 39 individuals used for the analysis of Lp-PLA2 mass, only 11 of which were

classified as having sleep apnea. Additionally, those that we did identify as having sleep

apnea, only exhibited a mild form of it with the average AHI being 12.4 ± 7.3. However,

it is informative that Lp-PLA2 levels are not altered in individuals with mild OSA. Lastly,

our subjects were recruited from a college campus, which likely led to the discrepancy in

age between the OSA and non-OSA groups (44.1 ± 12.9 years vs 28.6 ± 10.8 years).

In conclusion, our results showed no difference in Lp-PLA2 mass between OSA

and non-OSA subjects. When split up based on mean Lp-PLA2 mass, there was a

significant difference in waist circumference, sedentary time, and time spent in light

intensity physical activity, with MVPA and step count remaining the same between

30

groups. This suggests that abdominal fat as well as activity and sedentary time outside of

MVPA may be important in determining Lp-PLA2 concentration.

31

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Table 1. Subject characteristics between OSA and Non-OSA groups

OSA (n=11) Non-OSA (n=28)

Age 44.1 ± 12.9* 28.6 ± 10.8

AHI 12.4 ± 7.3 1.5 ± 1.2

Weight (kg) 95.4 ± 15.6 84.6 ± 17.9

Height (cm) 175.3 ± 9.6 169.7 ± 10.5

BMI 31.0 ± 4.7 29.7 ± 6.0

Waist (cm) 99.6 ± 12.1 91.5 ± 13.4

Neck (cm) 39.1 ± 4.5 36.0 ± 4.1

HR rest 68.2 ± 8.0 69.0 ± 11.0

*P=0.001 when compared to Non-OSA group

Table 2. Physical activity minutes between OSA and Non-OSA groups

OSA (n=8) Non-OSA (n=17)

Sedentary 815.3 ± 260.5* 754.3 ± 230.2

Light 123.9 ± 59.7 157.6 ± 87.5

Moderate 29.4 ± 9.7 42.7 ± 20.7

Vigorous 1.1 ± 2.4 3.6 ± 8.5

Very Vigorous 0.4 ± 0.5 0.2 ± 0.5

Total MVPA 32.9 ± 15.5 42.4 ± 26.5

Step Count 6303.1 ± 1440.9 7505.5 ± 2391.9

*P<0.05 when compared to Non-OSA group

37

Table 3. Subject characteristics between high and low Lp-PLA2 groups

Low Lp-PLA2

(n=20)

High Lp-PLA2

(n=19)

Age 31.6 ± 12.9 34.7 ± 14.0

AHI 3.4 ± 4.7 5.9 ± 7.6

BMI 28.5 ± 5.5 31.8 ± 5.4

Waist (cm) 87.8 ± 12.2 100.1 ± 11.9*

Total % Fat 32.7 ± 11.1 36.9 ± 11.9

*P<0.05 when compared to low Lp-PLA2 group

Table 4. Physical activity minutes between high and low Lp-PLA2 groups

Low Lp-PLA2

(n=14)

High Lp-PLA2

(n=11)

Sedentary 645.4 ± 161.3 937.3 ± 219.1*

Light 187.9 ± 84.5 94.6 ± 27.0*

Moderate 35.1 ± 17.7 42.6 ± 20.1

Vigorous 4.1 ± 9.3 1.1 ± 1.7

Total MVPA 39.4 ± 24.7 43.9 ± 20.7

Step Counts 7175.4 ± 2310.3 7051.1 ± 2108.4

*P<0.005 when compared to low Lp-PLA2 group

38

Figure 1. Lp-PLA2 mass values for the OSA and Non-OSA groups

Figure 2. Lp-PLA2 in relation to number of sedentary minutes per day.

0

100

200

300

400

500

600

200 400 600 800 1000 1200

Lp-P

LA2

mas

s (n

g/m

L)

Sedentary Minutes per Day

r=0.405

P<0.05

39

Appendix A. Informed Consent

Project Title: Does an Acute Bout of Exercise Reduce Exhaled Nitric Oxide Levels in Individuals with

Obstructive Sleep Apnea?

Consent to Participate in Research

Identification of Investigators & Purpose of Study You are being asked to participate in a research study conducted by Drs. Stephanie Kurti and Trent

Hargens from James Madison University. To participate, you must be in good health and not diagnosed

with any cardiovascular, pulmonary, or metabolic diseases (with the exception of Obstructive Sleep Apnea

(OSA)).

Previous research suggests that a bout of nighttime exercise was effective in reducing exhaled nitric oxide

levels in inactive asthmatic patients, which translated to improvements in pulmonary outcomes. However,

there is no literature that has shown if an acute bout of exercise lowers airway and systemic inflammation,

and improves vascular health in individuals with OSA. Therefore, the purpose of this study is to determine

whether an acute bout of exercise will reduce exhaled nitric oxide levels in individuals with OSA. This

study will contribute to the knowledge of both practitioners and clinicians, and may provide an important

public health message in providing exercise recommendations for those with elevated airway inflammation,

particularly in individuals with OSA. Should you decide to participate in this research study, you will be

asked to sign this consent form once all your questions have been answered to your satisfaction.

Research Procedures This study consists of four questionnaires, a body composition scan, an incremental exercise test to

exhaustion on a cycle ergometer, a home sleep evaluation device, a 7-day physical activity recording

device, and various physiological tests administered to individual participants in the Human Performance

Laboratory at James Madison University. The total time required for participation in the research study is

outlined on the following page (time required section).

Your will visit the laboratory a total of two times. The specific procedures during each visit are included

below:

Initial visit : On the first visit to the laboratory, you will be briefed on the study and asked to read and sign

a consent form and complete a health history questionnaire, as well as questionnaires assessing your

physical activity habits, daytime sleepiness, and snoring habits. If you’d like to see any of these

questionnaires prior to consenting, please ask a researcher and we’ll be happy to provide one for you.

After completion of the questionnaire, height, weight, and neck/waist circumference measurements will be

taken. We will then perform a fasted blood draw for Lp-PLA2. Following the blood draw, you will

complete two non-invasive breathing tests that will assess pulmonary function and airway inflammation.

Next, you will be asked to complete a maximal ramping exercise test, in which the resistance on the bike

will increase steadily until you say that you can no longer continue or cannot keep up, which should take

around 8 -15 minutes. We will be measuring some of your physiological responses continuously throughout

this test. At the end of this visit, you will be instructed how to properly set up and wear a home sleep

evaluation device to assess OSA. You will be asked to return with the device one day later.

Second visit: After returning with the sleep evaluation device one day after the initial visit, we’ll perform a

blood draw for Lp-PLA2. Then, we will perform a DEXA scan to assess your body composition (how

much of your body is fat vs. lean mass). Next, we will record your resting heart rate, heart rate variability,

and blood pressure, which will be obtained in the supine position. You will then be instructed how to

properly wear an accelerometer device (Actigraph GT-3X) to assess your 7-day physical activity. You will

return 8 days later for your control (CON) or Nighttime Exercise (NE) session

40

Participation in this study will require approximately 2 hours of your time in the lab over the course of 2

separate visits. The visits are outlined below:

Initial Visit : On the first visit to the laboratory, you will be asked to complete the required questionnaires

and have height, weight, and neck/waist circumference measurements taken. We will then complete a blood

draw and two non-invasive breathing tests. Also during the initial visit, you will be asked to complete the

incremental test to exhaustion. The entire testing day should take approximately 90 minutes.

Visit 2: You will be asked to return an ApneaLink device one day after your initial visit. Resting heart rate

and blood pressure and heart rate variability will be assessed followed by a DEXA scan. During this time,

you will also be instructed how to properly wear an accelerometer device. This visit should take

approximately 30 minutes.

Risks

Participation in this study does have some risks, although they are small. The risk of any serious event

during this study is very small. Possible risks include:

DEXA: The DEXA scan entails a low dose of radiation equivalent to approximately one transatlantic flight

(0.015 mSv= milliseievert). While there is no validated questionnaire to define extensive exposure,

radiation exposure is cumulative (200 DEXA scans is equal to the cumulative exposure of living at sea

level for a year (3 mSv). DEXA scans carry minimal X-ray exposure. To minimize exposure, the DEXA

scan will only be performed once. All body composition assessment will be performed according to the

American College of Sports Medicine guidelines for body composition assessment).

Blood sampling: The risks of blood sampling using venipuncture include possible mild bruising, and the

risk of transfer of blood-borne pathogens, as well as possible risks of infection or skin irritation. These risks

are considered to be minimal, and all safety precautions for handing blood samples will be followed

according to Occupational Safety and Health Administration (OSHA) protocols.

Benefits

By participating in this study, you may benefit by gaining knowledge of inflammatory markers, airway

inflammation (exhaled nitric oxide) and airway hyperresponsiveness, which provide important information

about your current cardiovascular and pulmonary health. You will learn your VO2peak, body composition,

and pulmonary function scores (forced expiratory flow in 1-sec, forced vital capacity, forced expiratory

flow at 25-75% of vital capacity). Society will benefit from more knowledge about how acute and chronic

exercise may benefit vascular and pulmonary outcomes in individuals with OSA.

Confidentiality The results of this research will be presented at the American College of Sports Medicine Annual meeting

as well as the American Society of Nutrition annual conferences. The results of this project will be coded in

such a way that the respondent’s identity will not be attached to the final form of this study. The researcher

retains the right to use and publish non-identifiable data. While individual responses are confidential,

aggregate data will be presented representing averages or generalizations about the responses as a whole.

All data will be stored in a secure location accessible only to the JMU researchers. Upon completion of the

study, all information that matches up individual respondents with their answers will be destroyed.

Participation & Withdrawal Your participation is entirely voluntary. You are free to choose not to participate. Should you choose to

participate, you can withdraw at any time without consequences of any kind.

41

Questions about the Study If you have questions or concerns during the time of your participation in this study, or after its completion

or you would like to receive a copy of the final aggregate results of this study, please contact:

Researcher’s Name:

Dr. Stephanie Kurti Department of Kinesiology

Email Address: kurtisp@jmu.edu James Madison University Cell-Phone number: 630-205-6363

Telephone: 540-568-3947

Researcher’s Name:

Dr. Trent Hargens Department of Kinesiology

E-mail Address: hargenta@jmu.edu James Madison Univeristy

Telephone: 540-568-5844

Questions about Your Rights as a Research Subject

Dr. Taimi Castle

Chair, Institutional Review Board

James Madison University (540) 568-5929 castletl@jmu.edu

Giving of Consent I have read this consent form and I understand what is being requested of me as a participant in this study. I

freely consent to participate. I have been given satisfactory answers to my questions. The investigator

provided me with a copy of this form. I certify that I am at least 18 years of age. ______________________________________

Name of Participant (Printed)

______________________________________ ______________

Name of Participant (Signed) Date

______________________________________ ______________

Name of Researcher (Signed) Date

42

Appendix B. PAR-Q+

43

44

45

46

Appendix C. IPAQ

INTERNATIONAL PHYSICAL ACTIVITY QUESTIONNAIRE (October 2002)

LONG LAST 7 DAYS SELF-ADMINISTERED FORMAT

FOR USE WITH YOUNG AND MIDDLE-AGED ADULTS (15-69 years)

The International Physical Activity Questionnaires (IPAQ) comprises a set of 4 questionnaires. Long (5 activity domains asked independently) and short (4 generic items) versions for use by either telephone or self-administered methods are available. The purpose of the questionnaires is to provide common instruments that can be used to obtain internationally comparable data on health–related physical activity.

Background on IPAQ The development of an international measure for physical activity commenced in Geneva in 1998 and was followed by extensive reliability and validity testing undertaken across 12 countries (14 sites) during 2000. The final results suggest that these measures have acceptable measurement properties for use in many settings and in different languages, and are suitable for national population-based prevalence studies of participation in physical activity.

Using IPAQ Use of the IPAQ instruments for monitoring and research purposes is encouraged. It is recommended that no changes be made to the order or wording of the questions as this will affect the psychometric properties of the instruments.

Translation from English and Cultural Adaptation Translation from English is encouraged to facilitate worldwide use of IPAQ. Information on the availability of IPAQ in different languages can be obtained at www.ipaq.ki.se. If a new translation is undertaken we highly recommend using the prescribed back translation methods available on the IPAQ website. If possible please consider making your translated version of IPAQ available to others by contributing it to the IPAQ website. Further details on translation and cultural adaptation can be downloaded from the website.

Further Developments of IPAQ International collaboration on IPAQ is on-going and an International Physical Activity Prevalence Study is in progress. For further information see the IPAQ website.

More Information More detailed information on the IPAQ process and the research methods used in the development of IPAQ instruments is available at www.ipaq.ki.se and Booth, M.L. (2000). Assessment of Physical Activity: An International Perspective. Research Quarterly for Exercise and Sport, 71 (2): s114-20. Other scientific publications and presentations on the use of IPAQ are summarized on the website.

47

INTERNATIONAL PHYSICAL ACTIVITY QUESTIONNAIRE

We are interested in finding out about the kinds of physical activities that people do as part of their everyday lives. The questions will ask you about the time you spent being physically active in the last 7 days. Please answer each question even if you do not consider yourself to be an active person. Please think about the activities you do at work, as part of your house and yard work, to get from place to place, and in your spare time for recreation, exercise or sport.

Think about all the vigorous and moderate activities that you did in the last 7 days. Vigorous physical activities refer to activities that take hard physical effort and make you breathe much harder than normal. Moderate activities refer to activities that take moderate physical effort and make you breathe somewhat harder than normal.

PART 1: JOB-RELATED PHYSICAL ACTIVITY

The first section is about your work. This includes paid jobs, farming, volunteer work, course work, and any other unpaid work that you did outside your home. Do not include unpaid work you might do around your home, like housework, yard work, general maintenance, and caring for your family. These are asked in Part 3.

1. Do you currently have a job or do any unpaid work outside your home? Yes

No Skip to PART 2: TRANSPORTATION

Yes

No Skip to PART 2: TRANSPORTATION

The next questions are about all the physical activity you did in the last 7 days as part of your paid or unpaid work. This does not include traveling to and from work.

2. During the last 7 days, on how many days did you do vigorous physical activities like heavy lifting, digging, heavy construction, or climbing up stairs as part of your work? Think about only those physical activities that you did for at least 10 minutes at a time.

_____ days per week

No vigorous job-related physical activity Skip to question 4

3. How much time did you usually spend on one of those days doing vigorous physical activities as part of your work?

_____ hours per day

_____ minutes per day

48

4. Again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate physical activities like carrying light loads as part of your work? Please do not include walking.

_____ days per week

No moderate job-related physical activity Skip to question 6

5. How much time did you usually spend on one of those days doing moderate physical activities as part of your work?

_____ hours per day

_____ minutes per day

6. During the last 7 days, on how many days did you walk for at least 10 minutes at a time as part of your work? Please do not count any walking you did to travel to or from work.

_____ days per week

No job-related walking Skip to PART 2: TRANSPORTATION

7. How much time did you usually spend on one of those days walking as part of your work?

_____ hours per day

_____ minutes per day

PART 2: TRANSPORTATION PHYSICAL ACTIVITY

These questions are about how you traveled from place to place, including to places like work, stores, movies, and so on.

8. During the last 7 days, on how many days did you travel in a motor vehicle like a train, bus, car, or tram?

_____ days per week

No traveling in a motor vehicle Skip to question 10

49

9. How much time did you usually spend on one of those days traveling in a train, bus, car, tram, or other kind of motor vehicle?

_____ hours per day

_____ minutes per day

Now think only about the bicycling and walking you might have done to travel to and from work, to do errands, or to go from place to place.

10. During the last 7 days, on how many days did you bicycle for at least 10 minutes at a time to go from place to place?

_____ days per week No bicycling from place to place Skip to question 12

No bicycling from place to place Skip to question 12

11. How much time did you usually spend on one of those days to bicycle from place to place?

_____ hours per day

_____ minutes per day

12. During the last 7 days, on how many days did you walk for at least 10 minutes at a time to go from place to place?

_____ days per week

No walking from place to place Skip to PART 3: HOUSEWORK, HOUSE MAINTENANCE, AND CARING FOR FAMILY

13. How much time did you usually spend on one of those days walking from place to place?

_____ hours per day

_____ minutes per day

PART 3: HOUSEWORK, HOUSE MAINTENANCE, AND CARING FOR FAMILY

This section is about some of the physical activities you might have done in the last 7 days in and around your home, like housework, gardening, yard work, general maintenance work, and caring for your family.

50

14. Think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do vigorous physical activities like heavy lifting, chopping wood, shoveling snow, or digging in the garden or yard?

_____ days per week

No vigorous activity in garden or yard Skip to question 16

15. How much time did you usually spend on one of those days doing vigorous physical activities in the garden or yard?

_____ hours per day

_____ minutes per day

16. Again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate activities like carrying light loads, sweeping, washing windows, and raking in the garden or yard?

_____ days per week

No moderate activity in garden or yard Skip to question 18

17. How much time did you usually spend on one of those days doing moderate physical activities in the garden or yard?

_____ hours per day

_____ minutes per day

18. Once again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate activities like carrying light loads, washing windows, scrubbing floors and sweeping inside your home?

_____ days per week

No moderate activity inside home Skip to PART 4: RECREATION, SPORT AND LEISURE-TIME PHYSICAL ACTIVITY

51

19. How much time did you usually spend on one of those days doing moderate physical activities inside your home?

_____ hours per day

_____ minutes per day

PART 4: RECREATION, SPORT, AND LEISURE-TIME PHYSICAL ACTIVITY

This section is about all the physical activities that you did in the last 7 days solely for recreation, sport, exercise or leisure. Please do not include any activities you have already mentioned.

20. Not counting any walking you have already mentioned, during the last 7 days, on how many days did you walk for at least 10 minutes at a time in your leisure time?

_____ days per week

No walking in leisure time Skip to question 22

21. How much time did you usually spend on one of those days walking in your leisure time?

_____ hours per day

_____ minutes per day

22. Think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do vigorous physical activities like aerobics, running, fast bicycling, or fast swimming in your leisure time?

_____ days per week

No vigorous activity in leisure time Skip to question 24

23. How much time did you usually spend on one of those days doing vigorous physical activities in your leisure time?

_____ hours per day

_____ minutes per day

52

24. Again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate physical activities like bicycling at a regular pace, swimming at a regular pace, and doubles tennis in your leisure time?

_____ days per week

No moderate activity in leisure time Skip to PART 5: TIME SPENT SITTING

25. How much time did you usually spend on one of those days doing moderate physical activities in your leisure time?

_____ hours per day

_____ minutes per day

PART 5: TIME SPENT SITTING

The last questions are about the time you spend sitting while at work, at home, while doing course work and during leisure time. This may include time spent sitting at a desk, visiting friends, reading or sitting or lying down to watch television. Do not include any time spent sitting in a motor vehicle that you have already told me about.

26. During the last 7 days, how much time did you usually spend sitting on a weekday?

_____ hours per day

_____ minutes per day

27. During the last 7 days, how much time did you usually spend sitting on a weekend day?

_____ hours per day

_____ minutes per day

This is the end of the questionnaire, thank you for participating.

LONG LAST 7 DAYS SELF-ADMINISTERED version of the IPAQ. Revised October 2002.

53

Appendix D. ESS

Epworth Sleepiness Scale

SubjectID______Name___________________________DateCompleted____/____/____

This questionnaire asks you to indicate the chances of you becoming drowsy during

hours of the day that you are not in bed sleeping. “How likely are you to doze off or

fall asleep in the following situations?”

Use the following scale and indicate the most appropriate number for each situation.

0 = would never doze

1 = slight chance of dozing

2 = moderate chance of dozing 3 = high chance of dozing

Situation Chance of dozing

1. Sitting and reading

_______

2. Watching T.V. _______

3. Sitting, inactive in a public place (ex.

Theatre or meeting)

_______

4. As a passenger in a car for an hour

without a break

_______

5. Lying down to rest in the afternoon when

circumstances permit

_______

6. Sitting and talking with someone _______

7. Sitting quietly after a lunch without

alcohol

_______

8. In a car, while stopped for a few minutes

in the traffic

_______

Sum of Scores, items 1-8 (staff use only) ______/24

54

Appendix E. Berlin Questionnaire

Berlin Questionnaire

Subject ID______ Name________________________ Date Completed ____/____/____

Height (cm) ___________Weight (kg) _________ Age _____

Please choose the correct response to each question. Category 1 Category 2 1. Do You Snore?

☐a.Yes

☐b.No

☐ c. Don’t know

6. How often do you feel tired or fatigued after you sleep?

☐ a. Nearly every day

☐ b. 3-4 times a week

☐ c. 1-2 times a week

☐ d. 1-2 times a month

☐ e. Never or nearly never

If you snore:

2. Your snoring is:

☐ a. Slightly louder than breathing

☐ b. As loud as talking

☐ c. Louder than talking

☐d.Very loud–can be heard in adjacent rooms

7. During your waking time, do you feel tired, fatigued or not up to par?

☐ a. Nearly every day

☐ b. 3-4 times a week

☐ c. 1-2 times a week

☐ d. 1-2 times a month

☐ e. Never or nearly never

3. How often do you snore?

☐ a. Nearly every day

☐ b. 3-4 times a week

☐ c. 1-2 times a week

☐ d. 1-2 times a month

☐ e. Never or nearly never

8. Have you ever nodded off or fallen asleep while driving a vehicle?

☐a.Yes

☐b.No

If yes:

4. Has your snoring every bothered other people?

☐a.Yes

☐b.No

☐ c. Don’t Know

9. How often does this occur?

☐ a. Nearly every day

☐ b. 3-4 times a week

☐ c. 1-2 times a week

☐ d. 1-2 times a month

☐ e. Never or nearly never 5. Has anyone noticed that you quit Breathing

during your sleep?

☐ a. Nearly every day

☐ b. 3-4 times a week

☐ c. 1-2 times a week

☐ d. 1-2 times a month

☐ e. Never or nearly never

Category 3 10. Do you have high blood pressure?

☐ a. Yes

☐ b. No

☐ c. Don’t Know

55

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